Article excerpt

Introduction

Access to basic health services of acceptable quality is still denied to many of the world's poorest people. (1) Against a backdrop of severely underfunded health systems, (1,2) governments are faced with a dilemma. Payments for health services, in the form of user charges, are likely to present a barrier to access. Yet, a shortage of resources at the facility level is a contributor to failure to deliver quality services, and this also presents a barrier to access. Some have argued that user charges can generate vital resources at the local level and help provide good quality services; (3-5) others have highlighted their negative effects, particularly on equity; (6-9) Recently, several international campaigns have advocated the removal of user fees, especially for primary care services. (1,10)

Some recent articles have underlined the paucity of evidence on the effectiveness of policy interventions in low-income countries; (11,12) others have noted the importance of systematic reviews for understanding health systems. (13) Despite the central importance of the user-fee debate, no systematic review has examined the quality of the empirical evidence on this topic. To redress this imbalance, this review set out to assess the quality of the existing evidence on the impact of user fees on health service utilization, household expenditures and health outcomes in low- and middle- income countries.

Methods

Scope of the review

User lees refer to a financing mechanism that has two main characteristics: payment is made at the point of service use and there is no risk sharing. User fees can entail any combination of drug costs, supply and medical material costs, entrance fees of consultation fees. They are typically paid for each visit to a health service provider, although in some cases follow-up visits for the same episode of illness can be covered by the initial payment. This review aimed to assess the effect on health service utilization of introducing, removing, increasing or decreasing user fees in low- and middle-income countries.

Search strategy and inclusion criteria

We searched 25 databases covering the social science, economics and health literature. We also searched the reference lists of all relevant articles, the web sites of related research centres or institutions (lists of sources searched are available from the authors upon request) and existing reviews. (14-19) The search strategy combined looking for terms in subject headings and within the text pertaining to health financing ("health financing", "user charges", "user fees", "cost recovery", "direct payment", "drug revolving fund", "fee") and outcomes ("utilization", "access to services", "health expenditures", etc.). No limitation on date or publication language was applied. Only studies from low- and middle-income countries, as defined by the World Bank, were included.

Only experimental or quasi-experimental study designs were included --cluster randomized controlled trials (C-RCTs), controlled "before and after" (CBA) studies and interrupted time series (ITS) studies (Table 1)--as suggested by the Effective Practice and Organisation of Care (EPOC) group of the Cochrane Collaboration, where this review was registered. Indeed, such designs are known to provide the most reliable measures of effect. Papers were assessed only if the effect of the intervention was measured in terms of either changes in utilization, household expenditure, health outcome or equity. Both authors independently sifted the titles and abstracts of publications for retrieval. In case of disagreement, full-text articles were retrieved and examined. All retrieved articles were then independently reviewed by the two authors, and agreement was reached over whether they fulfilled the criteria for inclusion in the review.

Reanalysis of data

We found several studies that had longitudinal data on utilization but had not performed a time series analysis, (20-26) To be able to include these, we relaxed the original definition of ITS (27) (Table 1) and set out to reanalyse the data appropriately. …